Natural language processing (NLP) systems are attempting to minimize uncertainty from reasoning through the use of known lexicons, ontologies, and corpora ingestion, but overall system accuracy using these known techniques has limitations. A known probabilistic distributed NLP system delivers answers to questions by parsing a natural language query in input text provided by a user, searching for multiple candidate answers to the query in its data set, and assigning confidence scores to the candidate answers. The probabilistic distributed NLP system can, in a limited way, take into account the context of the user who provided the input text if the context is appended to the query. Appending such context to a query, however, does not provide an ideal user experience because the combination of the query and the appended portion is not in the form of a question that would be posed naturally by a user. A known web search engine being utilized via a user's mobile device can take into account context consisting of the user's geographic location by processing search terms based in part on the user's location, which is provided by a global positioning system (GPS) incorporated into the device.